基于直方图分析和Jensen-Shannon散度的海表温度锋检测  

Sea surface temperature front detection based on histogram analysis and Jensen-Shannon divergence

作　　者：李阳东[1,2,3,4] 梁君豪 笪亨融 漆林 赵菊英 LI Yangdong;LIANG Junhao;DA Hengrong;QI Lin;ZHAO Juying(College of Marine Sciences,Shanghai Ocean University,Shanghai 201306,China;Key Laboratory of Oceanic Fisheries Exploration,Ministry of Agriculture and Rural Affaires,Shanghai 201306,China;Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources,Ministry of Education,Shanghai 201306,China;Shanghai Engineering Research Center of Estuarine and Oceanographic Mapping,Shanghai 201306,China)

机构地区：[1]上海海洋大学海洋科学学院,上海201306 [2]农业农村部大洋渔业开发重点实验室,上海201306 [3]大洋渔业资源可持续开发教育部重点实验室,上海201306 [4]上海市河口海洋测绘工程技术研究中心,上海201306

出　　处：《海洋测绘》2022年第4期60-64,共5页Hydrographic Surveying and Charting

基　　金：国家自然科学基金(42174016);国家重点研发计划(2019YFD0901404)。

摘　　要：海洋锋是海洋中的重要现象之一,通常可以利用锋面检测算法在遥感图像中进行提取。针对在海洋遥感图像质量较低、噪声较多的情况下梯度较小而尺度较大的海表面温度锋提取效果不佳的问题,对基于Jensen-Shannon散度的锋面提取方法进行了改进。具体改进是在计算图像散度时先进行直方图分析,即根据水温分布中的极小值对水温数据进行重新分组,然后使用新生成的水温分布来计算散度,另外还使用了Canny算法中的非极大值抑制对散度图中的锋面进行了细化。实验结果表明,改进后的方法提取出的锋面与使用梯度幅值表示的锋面基本吻合,同时比原方法更适合用于提取受噪声影响较多的水温图像中的大尺度锋面。Ocean fronts are one of the important phenomena in the ocean, and can generally be extracted from remote sensing images using a front detection algorithm.The extraction of sea surface temperature fronts with low gradient magnitude but large scale is often not satisfying in low-quality remote sensing images that heavily impacted by noise.To address this problem, this paper improves the Jensen-Shannon divergence based front detection method.The specific improvement is to perform histogram analysis when calculating divergence on the image, i.e.,the water temperature data is regrouped based on the local minimum value in the water temperature distribution, and then the regenerated water temperature distribution is used to calculate the divergence.In addition, non-maximum suppression is also used in the Canny algorithm to refine the fronts in the divergence matrix.The experimental results show that the fronts extracted by the improved method are substantially consistent with the fronts represented by gradient magnitude.Compared with the original method, the improved method is more suitable for extracting large-scale fronts in temperature images with a lot of noise.

关 键 词：海洋遥感 温度锋检测 直方图分析 Jensen-Shannon散度 非极大值抑制 

分 类 号：P229.7[天文地球—大地测量学与测量工程]